Lecture

Interspike Intervals & Renewal Processes

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Description

This lecture delves into the analysis of interspike intervals and renewal processes in neuronal dynamics, covering topics such as time-dependent renewal theory, firing probability in discrete time, and escape noise experiments. The instructor discusses the mathematical models of neurons, the firing probability, and the survivor function, providing insights into the stochastic nature of neuronal firing.

In MOOC

Neuronal Dynamics - Computational Neuroscience of Single Neurons

This course gives an introduction to the field of theoretical and computational neuroscience with a focus on models of single neurons. Neurons encode information about stimuli in a sequence of short electrical pulses (spikes).

Official source

Ontological neighbourhood

Statistics

Statistical inference: Mathematical statistics

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Computational neuroscience (also known as theoretical neuroscience or mathematical neuroscience) is a branch of neuroscience which employs mathematical models, computer simulations, theoretical analysis and abstractions of the brain to understand the principles that govern the development, structure, physiology and cognitive abilities of the nervous system. Computational neuroscience employs computational simulations to validate and solve mathematical models, and so can be seen as a sub-field of theoretical neuroscience; however, the two fields are often synonymous.

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